p53 expression, DNA content and cell proliferation in primary and synchronous metastatic lesions from ovarian surface epithelial-stromal tumours

The aim of this study was to investigate biological heterogeneity between primary and metastatic ovarian cancer lesions from individual patients as a means of elucidating steps in clinical progression. Cancer tissue from 61 untreated patients with ovarian surface epithelial-stromal tumours was examined. p53 expression detected immunocytochemically by the PAb1801 antibody, DNA content evaluated by flow cytometry, and cell proliferation evaluated as the [3H]thymidine labelling index were investigated in primary tumours and corresponding synchronous metastases. The frequency of p53 positivity was similar in primary (62%) and metastatic (66%) sites, with an agreement between the two lesions from the same patient in 97% of the cases. Similarly, aneuploidy frequency (80%) and DNA indices were superimposable in primary and metastatic lesions from the same patient, with a 94% agreement. The frequency of aneuploidy was higher in p53-positive than in p53-negative lesions. An overall poor agreement (rs = 0.44) was observed for proliferative activity of primary and metastatic lesions, due to a heterogeneous profile in omental with respect to primary tumours, which was mainly evident in p53-positive cancers. Conversely, cell proliferation of peritoneal, abdominal and pelvic lesions was qualitatively similar to that of the primary tumour in 88% of patients.     

Low prevalence of human papillomavirus in a geographic region with a high incidence of head and neck cancer

BACKGROUND: The main purpose of this study was to determine the prevalence of human papillomavirus (HPV) infection in patients with head and neck carcinomas from Brazil. MATERIALS AND METHODS: Forty-five patients with head and neck squamous cell carcinoma were included in the study, from 1995 to 1996. Forty-two were male and 3 female, with age ranging from 32 to 82 years (median 61). Five patients (11%) did not have previous history of use of tobacco and 38 (90.5%) were heavy smokers. Tumor sites were pyriform sinus, 10; tongue, 11 (oral, 6; base, 5); larynx, 7; floor of mouth, 3; tonsil, 6; retromolar area, 3; inferior gingiva 2; buccal mucosa, 2; and maxillary sinus in 1 patient. Twenty-five were stage IV, 17 stage III, and 3 stage II. RESULTS: The presence of HPV DNA was detected in 5 of 45 patients (11%), all of them with HPV 16. Two patients had HPV DNA in normal mucosa and tumor tissue, 1 patient had HPV DNA only in the normal mucosa and tumor tissue, 1 patient had HPV DNA only in the normal mucosa, and 2 patients were positive for HPV DNA in tumor tissue. Four patients were male and 1 was female; 2 patients were nonsmokers. Three patients had tonsil carcinoma, 1 patient had a tongue carcinoma, and 1 patient had a pyriform sinus cancer. CONCLUSIONS: The role of chemical carcinogens seems to be more important in the genesis of head and neck cancer than is HPV infection. The presence of HPV DNA in 5 of 45 patients stimulates further investigation to determine the role of HPV as a risk factor for head and neck carcinoma.     

Decoding two-dimensional complex multicomponent separations by autocovariance function

A new method for decoding two-dimensional (2D) multicomponent separations based on the use of the 2D Autocovariance function (2D-ACVF) has been developed. Theoretical models of single component (SC) spot distributions in 2D separations, both random and structured, are developed as the basis for a nonlinear estimation of both sample and separation system parameters from experimental 2D separations. The number of SCs, the average spot size, the spot capacity, and the saturation factor can be evaluated in the case of random SC spot patterns. The procedure was validated by extensive numerical simulation under conditions close to those usually found in GC x GC or 2D-polyacrylamid gel electrophoresis of proteins. The worse precision degree was no greater than 10% in the case of maximum spot density. This imprecision was fully accounted for, and it seems acceptable owing to the intrinsic statistical character of the estimation method. Structured multicomponent 2D separations, where SCs are linked by linear relationships, give rise to specific structured patterns in 2D-ACVF plots from which the parameters (phase and frequency) of the structured SC sequences can be evaluated: the study of 2D-ACVF makes it possible to decode multicomponent 2D separation, that is, to determine the number, relative abundance, and structural similarities of the single components. Pertinent expressions of the theoretical 2D-ACVF were derived for simple cases, and a procedure for decoding cases of structured 2D separations was developed and applied. It was shown that 2D separations containing both random and structured patterns of SC spots give rise to 2D-EACVF, which is the superimposition of the two component parts. This feature allows one, in principle, to decode the two components. The relevance of these results for Giddings sample dimensionality and separation dimensionality and their effective experimental evaluation is discussed.     

Poly(vinyl alcohol) as versatile biomaterial for potential biomedical applications

In this paper, we present some new case examples where the chemical versatility of poly (vinyl alcohol) (PVA) can be used for potential biomedical applications. PVA, the polymeric material used for designing new nanostructured devices, is water soluble, biocompatible and has excellent physical properties. We point out the possibility of obtaining wall-to-wall chemical hydrogels as well as microgels without diminishing the biocompatibility available in the starting PVA material. Injectability is another important factor to take into account in controlled drug delivery for gene therapy. In this respect, in this paper, established and more innovative methods are prospected in order to obtain particles with dimensions suitable for these applications.     

A cyclic CCK8 analogue selective for the cholecystokinin type A receptor: design, synthesis, NMR structure and binding measurements

A cyclic CCK8 analogue, cyclo(29,34)[Dpr(29),Lys(34)]-CCK8 (Dpr=L-2,3-diaminopropionic acid), has been designed on the basis of the NMR structure of the bimolecular complex between the N-terminal fragment of the CCK(A) receptor and its natural ligand CCK8. The conformational features of cyclo(29,34)[Dpr(29),Lys(34)]-CCK8 have been determined by NMR spectroscopy in aqueous solution and in water containing DPC-d(38) micelles (DPC=dodecylphosphocholine). The structure of the cyclic peptide in aqueous solution is found to be in a relaxed conformation, with the backbone and Dpr29 side chain atoms making a planar ring and the N-terminal tripeptide extending approximately along the plane of this ring. In DPC/water, the cyclic peptide adopts a "boat-shaped" conformation, which is more compact than that found in aqueous solution. The cyclic constraint between the Dpr29 side chain and the CCK8 carboxyl terminus (Lys34) introduces a restriction in the backbone conformational freedom. However, the interaction of cyclo(29,34)[Dpr(29),Lys(34)]-CCK8 with the micelles still plays an important role in the stabilisation of the bioactive conformation. A careful comparison of the NMR structure of the cyclic peptide in a DPC micelle aqueous solution with the structure of the rationally designed model underlines that the turn-like conformation in the Trp30-Met31 region is preserved, such that the Trp30 and Met31 side chains can adopt the proper spatial orientation to interact with the CCK(A) receptor. The binding properties of cyclo(29,34)[Dpr(29),Lys(34)]-CCK8 to the N-terminal receptor fragment have been investigated by fluorescence spectroscopy in a micellar environment. Estimates of the apparent dissociation constant, K(d), were in the range of 70-150 nM, with a mean value of 120+/-27 nM. Preliminary nuclear medicine studies on cell lines transfected with the CCK(A) receptor indicate that the sulfated-Tyr derivative of cyclo(29,34)[Dpr(29),Lys(34)]-CCK8 displaces the natural ligand with an IC(50) value of 15 microM.     

How you move reveals who you are: understanding human behavior by analyzing trajectory data

The widespread use of mobile devices is producing a huge amount of trajectory data, making the discovery of movement patterns possible, which are crucial for understanding human behavior. Significant advances have been made with regard to knowledge discovery, but the process now needs to be extended bearing in mind the emerging field of behavior informatics. This paper describes the formalization of a semantic-enriched KDD process for supporting meaningful pattern interpretations of human behavior. Our approach is based on the integration of inductive reasoning (movement pattern discovery) and deductive reasoning (human behavior inference). We describe the implemented Athena system, which supports such a process, along with the experimental results on two different application domains related to traffic and recreation management.     

Mapping Hurricane Katrina's widespread destruction in New Orleans using multisensor data and the normalized difference change detection (NDCD) technique

This paper introduces a new and general method for change detection based on the normalized difference change detection (NDCD) technique. A case study shows the use of the NDCD technique for flood mapping. Flood maps for the city of New Orleans (Louisiana, USA) resulting from the passage of Hurricane Katrina in 2005 were produced from the data processing of Satellite Pour l‘Observation de la Terre (SPOT)-4 High-Resolution Visible Infra-Red (HRVIR) and Landsat-5 Thematic Mapper (TM) images and the accuracies of the maps were verified using as ground truth the flood extension map of the city of New Orleans produced at the Dartmouth Flood Observatory (Dartmouth College, USA). The potentialities and performances of the NDCD technique in flood mapping were also compared to other standard change detection methods such as: (i) the near-infrared (NIR) normalized difference, (ii) unsupervised post-classification comparison, (iii) change vector analysis (CVA) and (iv) spectral–temporal minimum noise fraction (STMNF) transformation. When using the SPOT-4 HRVIR data, the NDCD technique led to better results than the other change detection methods considered here, while for the Landsat-5 TM data processing the closeness of the post-flood image to the Katrina landfall influenced the overall performances negatively. However, with respect to flood mapping in the urban area alone, which may be of major interest in most cases, the NDCD technique also performed better than all the other change detection methods considered here when using the Landsat-5 TM data.     

Neural network systems to reproduce crash behavior of structural components

The use of neural networks as global approximation tool in crashworthiness problems is here investigated. Neural networks are not only asked to return some meaningful indices of the structural behavior but also to reproduce load-time curves during crash phenomena. To contain the number of examples required for the training process, parallel subsystems of small neural networks are designed. Design points for the training process are obtained by explicit finite element analyses performed by PAMCRASH. The settlement of the points in the design domain is defined using a maximum distance concept. The procedure is applied to different typical absorption structures made of aluminum alloy: riveted tubes, honeycomb structures, longitudinal keel beam and intersection elements of helicopter subfloors.     

New N,O-containing ligands for the biomimetic copper-catalyzed polymerization of 2,6-dimethylphenol

Poly(2,6-dimethyl-1,4-phenylene ether) (PPE), which is widely used in high-performance engineering plastics, is obtained by the copper-catalyzed oxidative coupling of 2,6-dimethylphenol. The oxidative polymerizations have been carried out in acetonitrile with structurally related [copper-(N,O-containing ligand)] complexes as the catalyst precursor compounds, which appeared to be of great interest for a better understanding of the factors influencing the catalytic activities. Steric effects (influence of a methyl group close to the metal center; ligands 4–7) or electronic effects (imino versus amino group; ligands 4, 5, 8 and 6, 7, 9, respectively) on the polymerization rates have been demonstrated. The use of mono- or dinucleating ligands has strengthened the proposed mechanism of the reaction involving dinuclear active species.